Interactive Search Engine

1. A computer-implemented method for processing query data comprising: receiving, from a client over a network a portion of a query, wherein the portion of the query is not formerly issued by the user that initiated the query; before any predicted queries are provided to the client and in response to receiving the portion of the query determining, based on the portion of the query, a set of one or more predicted queries that correspond to the portion of the query; selecting, based upon selection criteria, a particular predicted query from the set of one or more predicted queries; processing the particular predicted query to obtain search results; and providing both the set of one or more predicted queries and the search results to the client over the network; wherein determining the set of one or more predicted queries includes: determining a plurality of potential predicted queries; for each query of the plurality of potential predicted queries: searching a first database to determine a first value that indicates how often said each query was issued during a first period of time; searching a second database to determine a second value that indicates how often said each query was issued during a second period of time that occurred temporally before or after the first period of time; scaling the first value by a scale factor to generate a scaled value: generating a resulting value based on the scaled value and the second value; and associating the resulting value with said each query: and using the resulting value of each query of the plurality of potential predicted queries to determine the set of one or more queries from the plurality of potential predicted queries.

2. The computer-implemented method as in claim 1 , wherein providing the set of one or more predicted queries to the client over the network further comprises: sending indication information with the one or more predicted queries based on how often the predicted queries issued in the past, wherein the indication information indicates an ordering of the set of one or more predicted queries in which the client may display the predicted queries.

3. The computer-implemented method as in claim 2 , wherein sending indication information with the set of one or more predicted queries is also based on when the predicted queries were issued.

4. The computer-implemented method as in claim 1 , wherein determining the set of one or more predicted queries that correspond to the portion of the query comprises: identifying key words in the portion of the query; and determining one or more predicted queries that correspond to the key words.

5. The computer-implemented method as in claim 1 , wherein: a query predictor determines the set of one or more predicted queries; and a search engine processes the particular predicted query to obtain the search results.

6. The computer-implemented method as in claim 5 , wherein: the particular predicted query is received from the client after the set of one or more predicted queries are provided to the client over the network; and the search results are subsequently sent to the client.

7. The computer-implemented method as in claim 5 , wherein the set of one or more predicted queries are provided to the client over the network at substantially the same time the particular predicted query is sent to the search engine.

8. The computer-implemented method as in claim 5 , wherein: receiving the portion of the query is performed by a front end server and includes the front end server sending the portion of the query to the query predictor; the front end server receives the set of one or more predicted queries from the query predictor and sends the particular predicted query to the search engine without sending the set of one or more predicted queries to the client; the front end server receives the search results from the search engine; and after receiving the search results from the search engine, the front end server subsequently provides both the set of one or more predicted queries and the search results to the client over the network.

9. The computer-implemented method as in claim 1 , further comprising providing to the client additional data, including advertisements, that relates to the search results.

10. The computer-implemented method of claim 1 , further comprising: receiving an indication of a selection of another predicted query in the set of one or more predicted queries; and providing new search results based on the selection of the selected predicted query.

11. The computer-implemented method of claim 1 , comprising the steps of: receiving from the client over the network the portion of the query and a subsequent portion of the query; determining a second set of one or more predicted queries that corresponds to the portion of the query and the subsequent portion of the query; and selecting, based upon selection criteria, a subsequent particular predicted query from the second set of one or more predicted queries, wherein the subsequent particular predicted query is not processed to obtain search results if the subsequent particular predicted query is the same as the previous particular predicted query.

12. The method of claim 1 , wherein the scale factor is a ratio of (a) a number of times a particular query is found in the first database to (b) a number of times said particular query is found in the second database, wherein none of the plurality of potential predicted queries is the particular query.

13. The method of claim 1 , wherein: generating the resulting value based on the scaled value and the second value includes weighting at least one of the scaled value or the second value by a weight factor to generate a second scaled value; the effect of the weight factor is to give more weight to temporally newer issued queries relative to temporally older issued queries; and the resulting value is also based on the second scaled value.

14. A machine-readable storage medium storing instructions which, when processed by one or more processors, causes the method of: receiving, from a client over a network a portion of a query, wherein the portion of the query is not formerly issued by the user that initiated the query; before any predicted queries are provided to the client and in response to receiving the portion of the query, determining, based on the portion of the query, a set of one or more predicted queries that correspond to the portion of the query; selecting, based upon selection criteria, a particular predicted query from the one or more predicted queries; processing the particular predicted query to obtain search results; and providing both the one or more predicted queries and the search results to the client over the network, wherein determining the set of one or more predicted Queries includes: determining a plurality of potential predicted queries; for each query of the plurality of potential predicted queries: search a first database to determine a first value that indicates how often said each query was issued during a first period of time; searching a second database to determine a second value that indicates how often said each query was issued during a second period of time that occurred temporally before or after the first period of time; scaling the first value by a scale factor to generate a scaled value; generating a resulting value based on the scaled value and the second value; and associating the resulting value with said each query; and using the resulting value of each query of the plurality of potential predicted queries to determine the set of one or more queries from the plurality of potential predicted queries.

15. The machine-readable storage medium of claim 14 , wherein providing the set of one or more predicted queries to the client over the network further comprises: sending indication information with the set of one or more predicted queries based on how often the predicted queries issued in the past, wherein the indication information indicates an ordering of the set of one or more predicted queries in which the client may display the predicted queries.

16. The machine-readable storage medium of claim 15 , wherein sending indication information with the set of one or more predicted queries is also based on when the predicted queries were issued.

17. The machine-readable storage medium of claim 14 , wherein determining one or more predicted queries that correspond to the portion of the query comprises: identifying key words in the portion of the query; and determining one or more predicted queries that correspond to the key words.

18. The machine-readable storage medium of claim 14 , wherein: a query predictor determines the set of one or more predicted queries; and a search engine processes the particular predicted query to obtain the search results.

19. The machine-readable storage medium of claim 18 , wherein: the particular predicted query is received from the client after the set of one or more predicted queries are provided to the client over the network; and the search results are subsequently sent to the client.

20. The machine-readable storage medium of claim 18 , wherein the set of one or more predicted queries are provided to the client over the network at substantially the same time the particular predicted query is sent to the search engine.

21. The machine-readable storage medium of claim 18 , wherein: receiving the portion of the query is performed by a front end server and includes the front end server sending the portion of the query to the query predictor; the front end server receives the set of one or more predicted queries from the query predictor and sends the particular predicted query to the search engine without sending the set of one or more predicted queries to the client; the front end server receives the search results from the search engine; and after receiving the search results from the search engine, the front end server subsequently provides both the set of one or more predicted queries and the search results to the client over the network.

22. The machine-readable storage medium of claim 14 , wherein the instructions, when processed by the one or more processors, further cause the method of providing to the client additional data, including advertisements, that relates to the search results.

23. The machine-readable storage medium of claim 14 , wherein the instructions, when processed by the one or more processors, further cause the method of: receiving an indication of a selection of another predicted query in the set of one or more predicted queries; and providing new search results based on the selection of the selected predicted query.

24. The machine-readable storage medium of claim 14 , wherein the instructions, when processed by the one or more processors, further cause the method of: receiving from the client over the network the portion of the query and a subsequent portion of the query; determining a second set of one or more predicted queries that corresponds to the portion of the query and the subsequent portion of the query; and selecting, based upon selection criteria, a subsequent particular predicted query from the second set of one or more predicted queries, wherein the subsequent particular predicted query is not processed to obtain search results if the subsequent particular predicted query is the same as the previous particular predicted query.

25. The machine-readable storage medium of claim 14 , wherein the scale factor is a ratio of (a) a number of times said each query is found in the first database to (b) a number of times said each query is found in the second database, wherein none of the plurality of potential predicted queries is the particular query.

26. The machine-readable storage medium of claim 14 , wherein: generating the resulting value based on the scaled value and the second value includes weighting at least one of the scaled value or the second value by a weight factor to generate a second scaled value; the effect of the weight factor is to give more weight to temporally newer issued queries relative to temporally older issued queries; and the resulting value is also based on the second scaled value.